Summary An important property of all cells is their ability to sense and respond to their environment. Often the appropriate response involves large scale changes in cell morphology. For example environmental cues, such as hormones or growth factors, can lead to cell differentiation, proliferation, or migration. These global changes in cell shape are highly coordinated and require dynamic regulation of the actin cytoskeleton. Therefore understanding how the actin cytoskeleton and associated regulatory proteins function as an integrated system is a central challenge for cell biology. The self-emergent properties of the cytoskeleton can only be understood with the aid of mathematical modeling and computational simulations. Using the interplay of theory and experiment, this project seeks to gain a mechanistic understanding of the oscillations in cell morphology that occur during cell rounding. We envision that as well as providing insight into a dynamic cytoskeletal system, this approach will provide insight into other fundamental biological processes, such as cell division and amoeboid migration. Moreover, because many disorders, including cancer, involve a dysregulation of the cytoskeleton, a mechanistic understanding of this system may lead to novel therapeutic strategies for treating disease. The overarching goals of this project are: 1) to understand how the actin cytoskeleton self-organizes to generate sustained oscillations in cell shape and 2) to develop mathematical models that predict the consequences of chemical and mechanical perturbations on the oscillatory behavior. The initial models will be developed to test our hypothesis that oscillations occur as a result of a traveling wave of RhoA activity. The wave front is propagated by a positive feedback loop involving the recruitment of guanine nucleotide exchange factors (GEFs), which accelerate activation of RhoA. A slow negative feedback loop involving GTPase activating proteins (GAPs), which deactivate RhoA, ensures RhoA activity remains localized as the wave travels. To test this hypothesis we have developed three aims that integrate experimental investigations with computational analysis and mathematical modeling. In Aim I single cell experiments are performed to characterize the dynamic structural and mechanochemical properties of oscillating cells and test model predictions. Proper utilization and interpretation o the data generated in Aim 1 requires the use of computational approaches. The development of advanced image processing tools is the focus of Aim 2. In Aim 3 multiphase models that spatially and temporally resolve chemical species, cell membranes, the cortex and cytosol are developed and tested through direct comparisons with the experimental results of Aim 1.